NEWS

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Rmlx 0.4.0

• mlx objects can now have row, column and dimnames, and vectors can have names. These work much like base R. Names for any dimension may be NULL. Subsetting with a non-existent name is an error. Many functions, e.g. solve(), %*%, etc. preserve dimnames like their R analogues.

Rmlx 0.3.0

• We now allow float64 arrays. (Note that mlx doesn't yet do operations on the gpu for these, however.)
• Breaking change: arrays no longer have an associated device. Instead, use mlx_device(), with_device() or local_device() to choose a device to work on. This also makes irrelevant a bug in which many/most operations were silently ignoring their operands' device.
• Operations which are currently cpu-only used to switch silently to cpu. They now take a device argument which must be explicitly set to "cpu". This is a teaching tool to help the user understand what operations can take place on which device.
• rbind() and cbind() now accept 1D vectors.
• Bugfix: mlx_expand_dims() works with 1D vectors.

Rmlx 0.2.3

• Speeded up single-axis [ subsetting by routing it through MLX take() instead of the generic meshgrid gather path.
• Added mlx_take_along_axis(), mlx_put_along_axis(), and mlx_scatter_add_axis() wrappers for MLX's axis-aligned indexed update ops.
• Added mlx_metal_kernel() to build custom Metal kernels from R and keep inputs and outputs as MLX arrays.
• Updated the bundled MLX source tarball and minimum supported MLX version to 0.31.1.
• Fixed the Linux bundled-build LAPACK shim for complex eigendecomposition and SVD entry points used by MLX 0.31.1.
• Fixed compatibility with MLX 0.31.1.
• Force clean recompilation when the detected MLX install or build flags change, avoiding stale object files after MLX upgrades.

Rmlx 0.2.2

Rmlx 0.2.1

Rmlx 0.2.0

Rmlx 0.1.0.9000

• Speeded up subset assignment. We also now fail on NAs in indices.
• Exposed mlx_cast() for casting arrays between dtypes/devices (previously internal .mlx_cast).
• %*% now requires both its arguments to be matrices (unlike base R).
• as_mlx(x) no longer returns scalars if x is a length-one vector.
• mlx_arange(start, stop, step) now matches seq() behavior (stop included if reachable).
• New mlx_device() to return device associated with x.
• Renamed mlx_get_device() to mlx_best_device().
• mlx_slice_update() now accepts 1-based (inclusive) start/stop indices to match the rest of the R API; internal callers were updated accordingly.
• Added mlx_shape() to expose MLX-native shapes (never NULL) and aligned dim.mlx() with base R semantics (returns NULL for 1-D vectors/scalars).
• mlx_rand_categorical(), mlx_rand_permutation(), mlx_cross_entropy(), mlx_gather_qmm(), and mlx_embedding() now accept 1-based indices for inputs/outputs, consistently with R.
• Added negative numeric indexing support for [/[<- on mlx arrays and documented subsetting semantics.
• Added mlx_import_function() to import MLX functions from (e.g.) Python.
• Added mlx_array(), mlx_matrix(), mlx_vector(), and mlx_scalar() for fast construction of MLX objects when data and dimensions are already known.
• mlx_array()/mlx_matrix() now recycle shorter payloads when they evenly divide the target shape.
• Added mlx_fft(), mlx_fft2(), and mlx_fftn() wrappers around MLX FFT kernels.
• Added distribution functions mlx_d/p/qnorm(), mlx_d/p/qunif() etc.
• Added mlx_quantile().
• Added mlx_coordinate_descent(), a coordinate descent algorithm.
• Fixed several [/[<- bugs affecting non-contiguous, unsorted, and duplicate subsetting patterns on mlx arrays.
• as_mlx() now takes a much faster path for large numeric matrices by letting MLX handle column-major inputs directly.
• Base reducers all() and any() applied to mlx arrays now return plain R logical scalars; mlx_all()/mlx_any() continue to yield mlx booleans.
• Added mlx-aware wrappers for row(), col(), asplit(), and backsolve().
• Added scale.mlx() to center/scale matrices entirely on the MLX backend (with MLX arrays stored in the scaled:center / scaled:scale attributes).
• scale.mlx() now always records its scaled:center / scaled:scale attributes as 1 x p MLX arrays, keeping them lazily evaluated even after coercion.
• as.matrix.mlx() now preserves any user-set attributes (including the MLX scaling metadata) when copying arrays back to base R.
• Created a new benchmarks vignette.
• Added pre-commit hooks to run, commit and print benchmark.

Rmlx 0.1.0

• Initial release on r-universe.